Antenna Season Report Notebook¶

Josh Dillon, Last Revised January 2022

This notebook examines an individual antenna's performance over a whole season. This notebook parses information from each nightly rtp_summarynotebook (as saved to .csvs) and builds a table describing antenna performance. It also reproduces per-antenna plots from each auto_metrics notebook pertinent to the specific antenna.

In [1]:
import os
from IPython.display import display, HTML
display(HTML("<style>.container { width:100% !important; }</style>"))
In [2]:
# If you want to run this notebook locally, copy the output of the next cell into the next line of this cell.
# antenna = "004"
# csv_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/_rtp_summary_'
# auto_metrics_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/auto_metrics_inspect'
# os.environ["ANTENNA"] = antenna
# os.environ["CSV_FOLDER"] = csv_folder
# os.environ["AUTO_METRICS_FOLDER"] = auto_metrics_folder
In [3]:
# Use environment variables to figure out path to the csvs and auto_metrics
antenna = str(int(os.environ["ANTENNA"]))
csv_folder = os.environ["CSV_FOLDER"]
auto_metrics_folder = os.environ["AUTO_METRICS_FOLDER"]
print(f'antenna = "{antenna}"')
print(f'csv_folder = "{csv_folder}"')
print(f'auto_metrics_folder = "{auto_metrics_folder}"')

antenna = "179"
csv_folder = "/home/obs/src/H6C_Notebooks/_rtp_summary_"
auto_metrics_folder = "/home/obs/src/H6C_Notebooks/auto_metrics_inspect"
In [4]:
display(HTML(f'<h1 style=font-size:50px><u>Antenna {antenna} Report</u><p></p></h1>'))

Antenna 179 Report

In [5]:
import numpy as np
import pandas as pd
pd.set_option('display.max_rows', 1000)
import glob
import re
from hera_notebook_templates.utils import status_colors, Antenna
In [6]:
# load csvs and auto_metrics htmls in reverse chronological order
csvs = sorted(glob.glob(os.path.join(csv_folder, 'rtp_summary_table*.csv')))[::-1]
print(f'Found {len(csvs)} csvs in {csv_folder}')
auto_metric_htmls = sorted(glob.glob(auto_metrics_folder + '/auto_metrics_inspect_*.html'))[::-1]
print(f'Found {len(auto_metric_htmls)} auto_metrics notebooks in {auto_metrics_folder}')

Found 31 csvs in /home/obs/src/H6C_Notebooks/_rtp_summary_
Found 29 auto_metrics notebooks in /home/obs/src/H6C_Notebooks/auto_metrics_inspect
In [7]:
# Per-season options
mean_round_modz_cut = 4
dead_cut = 0.4
crossed_cut = 0.0

def jd_to_summary_url(jd):
    return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H6C_Notebooks/blob/main/_rtp_summary_/rtp_summary_{jd}.html'

def jd_to_auto_metrics_url(jd):
    return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H6C_Notebooks/blob/main/auto_metrics_inspect/auto_metrics_inspect_{jd}.html'

Load relevant info from summary CSVs¶

In [8]:
this_antenna = None
jds = []

# parse information about antennas and nodes
for csv in csvs:
    df = pd.read_csv(csv)
    for n in range(len(df)):
        # Add this day to the antenna
        row = df.loc[n]
        if isinstance(row['Ant'], str) and '<a href' in row['Ant']:
            antnum = int(row['Ant'].split('</a>')[0].split('>')[-1]) # it's a link, extract antnum
        else:
            antnum = int(row['Ant'])
        if antnum != int(antenna):
            continue
        
        if np.issubdtype(type(row['Node']), np.integer):
            row['Node'] = str(row['Node'])
        if type(row['Node']) == str and row['Node'].isnumeric():
            row['Node'] = 'N' + ('0' if len(row['Node']) == 1 else '') + row['Node']
            
        if this_antenna is None:
            this_antenna = Antenna(row['Ant'], row['Node'])
        jd = [int(s) for s in re.split('_|\.', csv) if s.isdigit()][-1]
        jds.append(jd)
        this_antenna.add_day(jd, row)
        break
In [9]:
# build dataframe
to_show = {'JDs': [f'<a href="{jd_to_summary_url(jd)}" target="_blank">{jd}</a>' for jd in jds]}
to_show['A Priori Status'] = [this_antenna.statuses[jd] for jd in jds]

df = pd.DataFrame(to_show)

# create bar chart columns for flagging percentages:
bar_cols = {}
bar_cols['Auto Metrics Flags'] = [this_antenna.auto_flags[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jee)'] = [this_antenna.dead_flags_Jee[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jnn)'] = [this_antenna.dead_flags_Jnn[jd] for jd in jds]
bar_cols['Crossed Fraction in Ant Metrics'] = [this_antenna.crossed_flags[jd] for jd in jds]
bar_cols['Flag Fraction Before Redcal'] = [this_antenna.flags_before_redcal[jd] for jd in jds]
bar_cols['Flagged By Redcal chi^2 Fraction'] = [this_antenna.redcal_flags[jd] for jd in jds]
for col in bar_cols:
    df[col] = bar_cols[col]

z_score_cols = {}
z_score_cols['ee Shape Modified Z-Score'] = [this_antenna.ee_shape_zs[jd] for jd in jds]
z_score_cols['nn Shape Modified Z-Score'] = [this_antenna.nn_shape_zs[jd] for jd in jds]
z_score_cols['ee Power Modified Z-Score'] = [this_antenna.ee_power_zs[jd] for jd in jds]
z_score_cols['nn Power Modified Z-Score'] = [this_antenna.nn_power_zs[jd] for jd in jds]
z_score_cols['ee Temporal Variability Modified Z-Score'] = [this_antenna.ee_temp_var_zs[jd] for jd in jds]
z_score_cols['nn Temporal Variability Modified Z-Score'] = [this_antenna.nn_temp_var_zs[jd] for jd in jds]
z_score_cols['ee Temporal Discontinuties Modified Z-Score'] = [this_antenna.ee_temp_discon_zs[jd] for jd in jds]
z_score_cols['nn Temporal Discontinuties Modified Z-Score'] = [this_antenna.nn_temp_discon_zs[jd] for jd in jds]
for col in z_score_cols:
    df[col] = z_score_cols[col]

ant_metrics_cols = {}
ant_metrics_cols['Average Dead Ant Metric (Jee)'] = [this_antenna.Jee_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Dead Ant Metric (Jnn)'] = [this_antenna.Jnn_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Crossed Ant Metric'] = [this_antenna.crossed_metrics[jd] for jd in jds]
for col in ant_metrics_cols:
    df[col] = ant_metrics_cols[col]

redcal_cols = {}
redcal_cols['Median chi^2 Per Antenna (Jee)'] = [this_antenna.Jee_chisqs[jd] for jd in jds]
redcal_cols['Median chi^2 Per Antenna (Jnn)'] = [this_antenna.Jnn_chisqs[jd] for jd in jds]   
for col in redcal_cols:
    df[col] = redcal_cols[col]

# style dataframe
table = df.style.hide_index()\
          .applymap(lambda val: f'background-color: {status_colors[val]}' if val in status_colors else '', subset=['A Priori Status']) \
          .background_gradient(cmap='viridis', vmax=mean_round_modz_cut * 3, vmin=0, axis=None, subset=list(z_score_cols.keys())) \
          .background_gradient(cmap='bwr_r', vmin=dead_cut-.25, vmax=dead_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
          .background_gradient(cmap='bwr_r', vmin=crossed_cut-.25, vmax=crossed_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
          .background_gradient(cmap='plasma', vmax=4, vmin=1, axis=None, subset=list(redcal_cols.keys())) \
          .applymap(lambda val: 'font-weight: bold' if val < dead_cut else '', subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
          .applymap(lambda val: 'font-weight: bold' if val < crossed_cut else '', subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
          .applymap(lambda val: 'font-weight: bold' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
          .applymap(lambda val: 'color: red' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
          .bar(subset=list(bar_cols.keys()), vmin=0, vmax=1) \
          .format({col: '{:,.4f}'.format for col in z_score_cols}) \
          .format({col: '{:,.4f}'.format for col in ant_metrics_cols}) \
          .format('{:,.2%}', na_rep='-', subset=list(bar_cols.keys())) \
          .set_table_styles([dict(selector="th",props=[('max-width', f'70pt')])])

Table 1: Per-Night RTP Summary Info For This Atenna¶

This table reproduces each night's row for this antenna from the RTP Summary notebooks. For more info on the columns, see those notebooks, linked in the JD column.

In [10]:
display(HTML(f'<h2>Antenna {antenna}, Node {this_antenna.node}:</h2>'))
HTML(table.render(render_links=True, escape=False))

Antenna 179, Node N12:

Out[10]:
JDs A Priori Status Auto Metrics Flags Dead Fraction in Ant Metrics (Jee) Dead Fraction in Ant Metrics (Jnn) Crossed Fraction in Ant Metrics Flag Fraction Before Redcal Flagged By Redcal chi^2 Fraction ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score Average Dead Ant Metric (Jee) Average Dead Ant Metric (Jnn) Average Crossed Ant Metric Median chi^2 Per Antenna (Jee) Median chi^2 Per Antenna (Jnn)
2459845 digital_ok 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 0.849836 -0.500071 -0.387599 0.131923 4.502215 -1.573581 6.491174 -1.288290 0.7077 0.7301 0.4093 4.635185 5.101200
2459844 digital_ok 100.00% 100.00% 100.00% 0.00% - - 1.698743 2.806105 -0.055747 3.158749 14.882429 0.717759 3.015217 1.576994 0.0285 0.0265 0.0012 nan nan
2459843 digital_ok 100.00% 1.20% 0.66% 0.00% 100.00% 0.00% 0.961015 -0.434916 -1.170971 -1.207273 2.555120 -0.992306 6.734754 -0.519134 0.7251 0.7313 0.4162 4.407438 4.167485
2459842 digital_ok 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% -0.248377 -0.145069 0.214014 0.386481 4.191336 0.783581 1.253594 0.042971 0.7465 0.6561 0.2792 8.421163 8.957811
2459841 digital_ok 100.00% 100.00% 100.00% 0.00% - - 2.414631 3.634610 0.193135 2.110196 11.291602 1.224829 2.154852 1.822014 0.0284 0.0261 0.0016 nan nan
2459840 digital_ok 100.00% 100.00% 100.00% 0.00% - - 110.604897 312.120939 50.278546 206.291940 320.639267 6594.876550 697.918286 10379.717033 0.0450 0.0214 0.0065 nan nan
2459839 digital_ok 100.00% - - - - - 30.451380 41.386308 140.397816 196.027994 183.381509 413.744793 1268.352650 3081.952083 nan nan nan nan nan
2459838 digital_ok 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% -0.008735 0.286624 -0.898944 0.141224 7.428225 -1.639014 3.699609 -0.753475 0.6809 0.6452 0.4041 0.000000 0.000000
2459836 digital_ok - 100.00% 100.00% 0.00% - - nan nan nan nan nan nan nan nan 0.0379 0.0345 0.0023 nan nan
2459835 digital_ok 100.00% 100.00% 100.00% 0.00% - - -1.063875 -0.760086 -0.287293 -0.273706 12.557950 -1.272740 1.296011 -0.913938 0.0358 0.0352 0.0028 nan nan
2459833 digital_ok 100.00% 100.00% 100.00% 0.00% - - -0.483481 0.244014 0.443627 1.327881 12.148813 -0.389710 2.067507 1.449405 0.0367 0.0327 0.0019 nan nan
2459832 digital_ok 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% -0.195758 0.133129 -1.055984 -0.127496 3.396897 -1.190882 7.094316 -0.550181 0.7409 0.4696 0.5550 3.318981 3.035978
2459831 digital_ok 100.00% 100.00% 100.00% 0.00% - - -0.085597 0.732906 1.789859 6.045606 1.610739 0.936051 1.367570 2.287349 0.0391 0.0322 0.0038 nan nan
2459830 digital_ok 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% -0.121219 1.152893 -1.055763 0.021338 6.891660 -1.530655 7.063952 -1.058322 0.7450 0.4867 0.5402 4.885598 5.100486
2459829 digital_ok 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% -0.714255 2.195250 -0.417459 0.088382 3.693709 -1.706710 10.711215 -0.868631 0.6973 0.6126 0.4078 8.797915 5.291812
2459828 digital_ok 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% -0.485859 1.062711 -0.527006 0.123087 4.961027 -0.701746 5.909206 -0.669232 0.7384 0.4894 0.5210 0.000000 0.000000
2459827 digital_ok 0.00% 100.00% 100.00% 0.00% 100.00% 0.00% -0.104599 1.163918 -0.792024 0.067664 2.194970 -0.781281 0.681099 -1.478662 0.0640 0.0643 0.0120 -0.000000 -0.000000
2459826 digital_ok 100.00% 100.00% 100.00% 0.00% 100.00% 0.00% 0.421057 0.313596 -0.570132 -0.080555 8.117856 -1.329655 14.226338 -0.358397 0.0711 0.0831 0.0178 0.000000 0.000000
2459825 digital_ok 100.00% 100.00% 100.00% 0.00% 100.00% 0.00% -0.085908 -0.299432 -0.512978 0.181104 3.644161 -0.750996 0.201771 -0.809213 0.0734 0.0744 0.0181 1.190762 1.193227
2459824 digital_ok 100.00% 100.00% 100.00% 0.00% 100.00% 0.00% 0.485771 0.864506 -0.555155 0.348550 5.114376 -1.132097 8.157282 -0.598949 0.0684 0.0692 0.0117 0.955371 0.952720
2459823 digital_ok 100.00% 100.00% 100.00% 0.00% 100.00% 0.00% 2.002835 -0.135416 -0.340247 -0.024544 0.750044 -0.033247 9.849564 0.163716 0.0651 0.0707 0.0171 0.877384 0.882741
2459822 digital_ok 100.00% 100.00% 100.00% 0.00% 100.00% 0.00% -0.344974 0.823320 -0.940155 0.121739 4.012698 -0.962325 4.379445 -0.744692 0.0653 0.0702 0.0129 1.186536 1.189353
2459821 digital_ok 0.00% 100.00% 100.00% 0.00% 100.00% 0.00% -0.712995 -0.565067 -0.934483 -0.270213 2.070449 -0.596374 1.609851 -0.615560 0.0520 0.0623 0.0121 1.236261 1.235982
2459820 digital_ok 100.00% 100.00% 100.00% 0.00% 100.00% 0.00% -0.138878 0.929840 -0.733980 -0.139017 5.522436 0.119448 6.961818 -0.044019 0.0640 0.0655 0.0112 1.213106 1.211349
2459817 digital_ok 0.00% 100.00% 100.00% 0.00% 100.00% 0.00% -0.793452 0.337476 -0.930570 -0.205615 0.433579 -0.792208 0.299115 -0.806917 0.0722 0.0847 0.0150 1.207773 1.211174
2459816 digital_ok 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 0.829031 0.639867 -0.669125 0.375458 4.316428 0.418771 9.245096 -0.186388 0.8389 0.5835 0.6056 3.693647 3.710528
2459815 digital_ok 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% -0.385011 0.014002 -0.761165 -0.044224 4.543640 -0.069163 6.629410 -0.303116 0.7896 0.6523 0.5300 3.157788 3.126359
2459814 digital_ok 0.00% - - - - - nan nan nan nan nan nan nan nan nan nan nan nan nan
2459813 digital_ok 100.00% 100.00% 100.00% 0.00% 100.00% 0.00% nan nan inf inf nan nan nan nan nan nan nan 0.000000 0.000000

Load antenna metric spectra and waterfalls from auto_metrics notebooks.¶

In [11]:
htmls_to_display = []
for am_html in auto_metric_htmls:
    html_to_display = ''
    # read html into a list of lines
    with open(am_html) as f:
        lines = f.readlines()
    
    # find section with this antenna's metric plots and add to html_to_display
    jd = [int(s) for s in re.split('_|\.', am_html) if s.isdigit()][-1]
    try:
        section_start_line = lines.index(f'<h2>Antenna {antenna}: {jd}</h2>\n')
    except ValueError:
        continue
    html_to_display += lines[section_start_line].replace(str(jd), f'<a href="{jd_to_auto_metrics_url(jd)}" target="_blank">{jd}</a>')
    for line in lines[section_start_line + 1:]:
        html_to_display += line
        if '<hr' in line:
            htmls_to_display.append(html_to_display)
            break

Figure 1: Antenna autocorrelation metric spectra and waterfalls.¶

These figures are reproduced from auto_metrics notebooks. For more info on the specific plots and metrics, see those notebooks (linked at the JD). The most recent 100 days (at most) are shown.

In [12]:
for i, html_to_display in enumerate(htmls_to_display):
    if i == 100:
        break
    display(HTML(html_to_display))

Antenna 179: 2459845

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
179 N12 digital_ok ee Temporal Discontinuties 6.491174 -0.500071 0.849836 0.131923 -0.387599 -1.573581 4.502215 -1.288290 6.491174

Antenna 179: 2459844

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
179 N12 digital_ok ee Temporal Variability 14.882429 1.698743 2.806105 -0.055747 3.158749 14.882429 0.717759 3.015217 1.576994

Antenna 179: 2459843

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
179 N12 digital_ok ee Temporal Discontinuties 6.734754 -0.434916 0.961015 -1.207273 -1.170971 -0.992306 2.555120 -0.519134 6.734754

Antenna 179: 2459842

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
179 N12 digital_ok ee Temporal Variability 4.191336 -0.248377 -0.145069 0.214014 0.386481 4.191336 0.783581 1.253594 0.042971

Antenna 179: 2459841

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
179 N12 digital_ok ee Temporal Variability 11.291602 2.414631 3.634610 0.193135 2.110196 11.291602 1.224829 2.154852 1.822014

Antenna 179: 2459840

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
179 N12 digital_ok nn Temporal Discontinuties 10379.717033 110.604897 312.120939 50.278546 206.291940 320.639267 6594.876550 697.918286 10379.717033

Antenna 179: 2459839

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
179 N12 digital_ok nn Temporal Discontinuties 3081.952083 41.386308 30.451380 196.027994 140.397816 413.744793 183.381509 3081.952083 1268.352650

Antenna 179: 2459838

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
179 N12 digital_ok ee Temporal Variability 7.428225 0.286624 -0.008735 0.141224 -0.898944 -1.639014 7.428225 -0.753475 3.699609

Antenna 179: 2459835

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
179 N12 digital_ok ee Temporal Variability 12.557950 -0.760086 -1.063875 -0.273706 -0.287293 -1.272740 12.557950 -0.913938 1.296011

Antenna 179: 2459833

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
179 N12 digital_ok ee Temporal Variability 12.148813 0.244014 -0.483481 1.327881 0.443627 -0.389710 12.148813 1.449405 2.067507

Antenna 179: 2459832

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
179 N12 digital_ok ee Temporal Discontinuties 7.094316 -0.195758 0.133129 -1.055984 -0.127496 3.396897 -1.190882 7.094316 -0.550181

Antenna 179: 2459831

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
179 N12 digital_ok nn Power 6.045606 -0.085597 0.732906 1.789859 6.045606 1.610739 0.936051 1.367570 2.287349

Antenna 179: 2459830

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
179 N12 digital_ok ee Temporal Discontinuties 7.063952 -0.121219 1.152893 -1.055763 0.021338 6.891660 -1.530655 7.063952 -1.058322

Antenna 179: 2459829

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
179 N12 digital_ok ee Temporal Discontinuties 10.711215 2.195250 -0.714255 0.088382 -0.417459 -1.706710 3.693709 -0.868631 10.711215

Antenna 179: 2459828

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
179 N12 digital_ok ee Temporal Discontinuties 5.909206 1.062711 -0.485859 0.123087 -0.527006 -0.701746 4.961027 -0.669232 5.909206

Antenna 179: 2459827

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
179 N12 digital_ok ee Temporal Variability 2.194970 -0.104599 1.163918 -0.792024 0.067664 2.194970 -0.781281 0.681099 -1.478662

Antenna 179: 2459826

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
179 N12 digital_ok ee Temporal Discontinuties 14.226338 0.313596 0.421057 -0.080555 -0.570132 -1.329655 8.117856 -0.358397 14.226338

Antenna 179: 2459825

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
179 N12 digital_ok ee Temporal Variability 3.644161 -0.299432 -0.085908 0.181104 -0.512978 -0.750996 3.644161 -0.809213 0.201771

Antenna 179: 2459824

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
179 N12 digital_ok ee Temporal Discontinuties 8.157282 0.485771 0.864506 -0.555155 0.348550 5.114376 -1.132097 8.157282 -0.598949

Antenna 179: 2459823

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
179 N12 digital_ok ee Temporal Discontinuties 9.849564 -0.135416 2.002835 -0.024544 -0.340247 -0.033247 0.750044 0.163716 9.849564

Antenna 179: 2459822

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
179 N12 digital_ok ee Temporal Discontinuties 4.379445 -0.344974 0.823320 -0.940155 0.121739 4.012698 -0.962325 4.379445 -0.744692

Antenna 179: 2459821

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
179 N12 digital_ok ee Temporal Variability 2.070449 -0.565067 -0.712995 -0.270213 -0.934483 -0.596374 2.070449 -0.615560 1.609851

Antenna 179: 2459820

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
179 N12 digital_ok ee Temporal Discontinuties 6.961818 -0.138878 0.929840 -0.733980 -0.139017 5.522436 0.119448 6.961818 -0.044019

Antenna 179: 2459817

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
179 N12 digital_ok ee Temporal Variability 0.433579 -0.793452 0.337476 -0.930570 -0.205615 0.433579 -0.792208 0.299115 -0.806917

Antenna 179: 2459816

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
179 N12 digital_ok ee Temporal Discontinuties 9.245096 0.639867 0.829031 0.375458 -0.669125 0.418771 4.316428 -0.186388 9.245096

Antenna 179: 2459815

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
179 N12 digital_ok ee Temporal Discontinuties 6.629410 0.014002 -0.385011 -0.044224 -0.761165 -0.069163 4.543640 -0.303116 6.629410

Antenna 179: 2459814

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
179 N12 digital_ok nn Shape nan nan nan nan nan nan nan nan nan

Antenna 179: 2459813

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
179 N12 digital_ok nn Shape nan nan nan inf inf nan nan nan nan
In [ ]: